Design and implement data storage, data processing, and data security solutions using Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Data Lake Storage Gen2, Event Hubs, and Stream Analytics — from batch pipelines to real-time streaming at scale.
From partition strategies and data lake design to batch and stream pipelines, data security, performance optimisation, and full pipeline monitoring — every DP-203 domain with real labs.
Design partition strategies for files, analytical, and streaming workloads; build the data exploration layer with Synapse serverless SQL and Spark; ingest and transform data using ADF, Spark, T-SQL, and Stream Analytics; develop batch pipelines with Delta Lake and Azure Databricks; build stream processing with Event Hubs; implement data security, monitoring, and optimisation — the full DP-203 engineering lifecycle.
Implement partition strategies for files, analytical, streaming workloads, and Azure Synapse Analytics; identify when ADLS Gen2 partitioning is needed.
Design incremental loads, transform with Apache Spark and T-SQL, handle duplicates, missing data, late-arriving data, and JSON shredding.
Stream Analytics, Event Hubs, Spark Structured Streaming, windowed aggregates, time series, watermarking, and exactly-once delivery.
Implement data masking, encryption at rest and in motion, row-level and column-level security, POSIX-like ACLs for ADLS Gen2, data retention policies, secure endpoints, and resource tokens in Azure Databricks.
Implement Azure Monitor logging, measure data movement and query performance, schedule pipeline tests, implement pipeline alert strategies, compact files, and handle skew and spill.
Develop batch solutions with ADLS, Databricks, Synapse, and ADF. Use PolyBase, implement Synapse Link, read/write Delta Lake, upsert data.
Create and execute queries using SQL serverless pools and Spark clusters, recommend and implement Azure Synapse Analytics database templates, push data lineage to Microsoft Purview, and browse and search metadata in the Microsoft Purview Data Catalog — full data governance and discovery for the modern data lakehouse.
Data engineering is the foundation of every analytics and AI initiative. DP-203 proves you can build, operate, and optimise enterprise-scale data pipelines on Azure's most powerful data services.
Azure Synapse, Databricks, Data Lake Gen2, ADF, Event Hubs, Stream Analytics, and Delta Lake — all in one certification.
Data engineers are the most hired data professionals globally — earning consistently higher salaries than analysts and BI developers.
DP-203 uniquely covers all three modern data patterns — MDW, big data lakehouse, and real-time streaming — in full depth.
Row-level security, encryption, POSIX ACLs, data masking, and Microsoft Purview governance are woven into every pipeline design.
DP-203 is the recommended stepping stone to DP-100 (Data Scientist) and Azure Data Architect roles for ambitious data professionals.
From data lake partition strategies and exploration to batch pipelines, stream processing, data security, monitoring, and performance optimisation.
Flexible pricing for video, live, and blended training modes — we reply within 24 hours.
Azure Data Engineers are among the highest-paid technology professionals, working at tech companies, banks, retail giants, telecom firms, and analytics consultancies globally.
Join data engineers who power analytics, AI, and business intelligence at scale — using Azure's most powerful data engineering platform.